NAMD and VMD provide state-of-the-art molecular simulation, analysis, and visualization tools that leverage a panoply of GPU acceleration technologies to achieve performance levels that enable scientists to routinely apply research methods that were formerly too computationally demanding to be practical. To make state-of-the-art MD simulation and computational microscopy workflows available to a broader range of molecular scientists including non-traditional users of HPC systems, our center has begun producing pre-configured container images and Amazon EC2 AMIs that streamline deployment, particularly for specialized occasional-use workflows, e.g., for refinement of atomic structures obtained through cryo-electron microscopy. This talk will describe the latest technological advances in NAMD and VMD, using CUDA, OpenACC, and OptiX, including early results on ORNL Summit, state-of-the-art RTX hardware ray tracing on Turing GPUs, and easy deployment using containers and cloud computing infrastructure.
We'll showcase recent successes in the use of GPUs to accelerate challenging molecular simulation analysis tasks on the latest NVIDIA?Tesla?P100 GPUs on both Intel and IBM/OpenPOWER hardware platforms, and large-scale runs on petascale computers such as Titan and Blue Waters. We'll highlight the performance benefits obtained from die-stacked memory on the Tesla P100, the NVIDIA NVLink# interconnect on the IBM "Minsky" platform, and the use of NVIDIA CUDA?just-in-time compilation to increase the performance of data-driven algorithms. We will present results obtained with OpenACC parallel programming directives, current challenges, and future opportunities. Finally, we'll describe GPU-accelerated machine learning algorithms for tasks such as clustering of structures resulting from molecular dynamics simulations.
The tremendous successes that GPUs have had in accelerating molecular simulations must continue to be matched by advances in their application to challenging simulation preparation, analysis, and visualization tasks. We will describe how the latest developments in the molecular visualization tool VMD exploit GPUs using exciting new features of CUDA, OpenACC, EGL, and OptiX to accelerate key science tasks on clouds, clusters, and petascale computers. We will summarize our early experiences and performance results on GPU-accelerated OpenPOWER platforms with an eye toward the challenges and opportunities posed by the upcoming DOE Summit and Sierra systems.
We'll showcase recent successes in the use of GPUs to accelerate challenging molecular visualization and analysis tasks on hardware platforms ranging from commodity desktop computers to the latest GPU-accelerated petascale supercomputers by Cray and IBM. We'll highlight the use of in-situ ray tracing and rasterization combined with GPU-accelerated video streaming for high-interactivity remote visualization, CUDA just-in-time compilation to increase the performance of data-driven visualization and analysis algorithms, and we'll describe new, GPU-accelerated, MD trajectory clustering algorithms.
VMD is a tool for preparing, analyzing, and visualizing molecular dynamics simulations, with particular emphasis on large biomolecular systems, including drug targets such as the bacterial ribosome, and large viruses such as HIV.The computational challenges posed by large simulations present a significant hurdle for simulation and analysis tools. GPUs provide unprecedented computational capabilities at a very low cost, making it possible for applications like VMD to accelerate tasks that would otherwise be beyond our grasp. The ubiquitous nature of powerful GPUs on hardware ranging from tablets to supercomputers has allowed us to make a significant investment in developing GPU algorithms for a broad range of uses covering everything from ion placement during simulation preparation to photorealistic ray tracing of movies on hundreds of supercomputer nodes.Join us for this webinar as John Stone, Senior Research Programmer, University of Illinois provides an overview of the GPU-accelerated features of VMD and how they can be used to speed up a wide range of simulation preparation, analysis, and visualization tasks today, along with a roadmap of things to come in the future.
Molecular dynamics simulations provide a powerful tool for probing the dynamics of cellular processes at atomic and nanosecond resolution not achievable by experimental methods alone. We describe how GPU-accelerated petascale supercomputers are enabling studies of large biomolecular systems such as the HIV virus in all-atom detail for the first time.
This talk will present recent successes in the use of GPUs to accelerate interactive molecular visualization and analysis tasks on hardware platforms ranging from commodity desktop computers to the latest Cray XK7 supercomputers. The talk will focus on recent algorithm algorithm developments and the applicability and efficient use of new CUDA features on state-of-the-art Kepler GPUs. Will present the latest performance results for GPU accelerated trajectory analysis runs on the Blue Waters Cray XK7 and other GPU-accelerated HPC platforms, and conclude with a discussion of ongoing work and future opportunities for GPU acceleration, particularly as applied to the analysis of petascale simulations of large biomolecular complexes and long simulation timescales.
This talk will present recent successes in the use of GPUs to accelerate interactive molecular visualization and analysis tasks on desktop computers, and batch-mode simulation and analysis jobs on GPU-accelerated HPC clusters. We'll present Fermi-specific algorithms and optimizations and compare with those for other devices. We'll also present performance and performance/watt results for VMD analysis calculations on GPU clusters, and conclude with a discussion of ongoing work and future opportunities for GPU acceleration, particularly as applied to the analysis of petascale simulations of large biomolecular complexes and long simulation timescales.